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🤖New blog post🤖
AlphaFold 2 refines protein structures in an iterative, equivariant way. @FabianFuchsML and I wrote about the challenges of building an iterative, equivariant SE(3)-Transformer. Complete with code and a tech report!
edwag.github.io/se3iterative
imma be honest. i think if u work at anthropic rn u should be pushing leadership *as hard as u possibly can* to implement and publicly announce a parallel pause.
i realize there are maybe some reasons not to. maybe u don't really think openai is actually doing that much, maybe u think this is to some extent just marketing, maybe u think they paused one run but probably have many other more relevant ones going. maybe u think they did in fact pause but only bc ur ahead, and a brief delay could let them seize control of the situation. maybe u just think u have better aligned models and better sandboxing and monitoring already, and u don't need any such pause.
sure. this might all be true.
but u have said, often, from the beginning, that some level of coordinated slowdown and pause at points of danger is exactly what you want. u have said it publicly, ur c-suite, ur founders, ur official communications, ur employees, in the distant past and just weeks ago. and regardless of the overall impact, regardless of exactly what openai is doing, the public costly signal that u are willing to *actually do this* would be incredibly important. it would start to build trust that this isn't just marketing, it isn't just a game, that despite the intense rivalry there *is* a chance at coordination here. obviously these sorts of vague, open-ended, low-visibility company initiated pauses aren't what we need as a long term solution. but action like this is *what real solutions are built on top of*.
take a chance on it
We have paused some frontier RL training to ensure that we can meet the appropriate alignment, security and monitoring standards for the new level of capabilities in front of us. Model progress is now extremely rapid, and we always said we would take action if we felt that model capabilities were outstripping the pace of safety and alignment.
We care very deeply about AI safety. We believe the entire field will have to coordinate on shared safety standards, but will act unilaterally in the meantime.
We expect confidence in safety to increasingly set the pace of AI progress. We are optimistic about the alignment work we are doing, and we remain committed to making frontier capabilities widely available.
openai.com/index/pacing-mode…
Ed Wagstaff retweeted
I wrote a blog post trying to understand TrackStar, a gradient-based method tracing LLM predictions to influential training examples.
Mostly: take the main equation, read it from right to left, and poke at the pieces with a small MNIST toy example. 🙂
☕️ fabianfuchsml.github.io/trac…
Ed Wagstaff retweeted
I will be giving an overview of what we are up to @PrescientDesign during my talk @CCG_MOE #BiologicsByDesign2023 #proteinengineering #machinelearning #proteindesign
Ed Wagstaff retweeted
🕸️ In "Learnable Commutative Monoids for Graph Neural Networks", Euan Ong and I show how to build potent, learnable and aligned aggregators for GNNs, building on the success of PNA (@GabriCorso @dom_beaini) and set aggregation (@EdWagstaff @FabianFuchsML @martinengelcke).
Ed Wagstaff retweeted
📢 New blog post!
Realising an intricate connection between PNA (@GabriCorso @lukecavabarrett @dom_beaini @pl219_Cambridge) & the seminal work on set representations (Wagstaff @FabianFuchsML @martinengelcke @IngmarPosner @maosbot), Fabian and I join forces to attempt to explain!
I have recently had a range of very insightful conversations with @PetarV_93 about graph neural networks, networks on sets, universality and how ideas have spread in the two communities. This is our write up, feedback welcome as always! :)
➡️fabianfuchsml.github.io/univ… ☕️
Ed Wagstaff retweeted
BayesOpt is great for exploring the unknown, but it's hard to know when you're accurately predicting new inputs. Two big reasons it's hard --- faulty assumptions and covariate shift. Our new preprint shows conformal prediction can improve coverage!
arxiv.org/abs/2210.12496
1/7
I've seen plenty of people flatly dismissing these sorts of concerns as "sci-fi", but no substantive arguments that they shouldn't be taken seriously. That's partly because I don't really know where to look for such arguments. Are there any?
Ed Wagstaff retweeted
It is w pride (and a tear in my eye) that after 6 months of competitive assessment, negotiations & legal due diligence, I can announce that @esa has awarded a €1M contract to a program I am leading in consortium with @CompSciOxford @isp_uv_es @BrockmannCon,
project #OpenSR
Ed Wagstaff retweeted
I'm hiring for Research Scientist and Research Engineer roles on the Alignment team at DeepMind! Come talk to me at the EA Global London career fair (4-8 pm Friday 15 April), or DM / email me and I can let you know when the job ad officially goes up.
Ed Wagstaff retweeted
Graph neural networks often have to globally aggregate over all nodes. How we do this can have a significant impact on performance 🎯. After we recently finished a project on this, I wrote a blog post on this topic. Let me know what you think! :)
➡️fabianfuchsml.github.io/equi… ☕️
Ed Wagstaff retweeted
Multiple open faculty positions at @CompSciOxford - join a great CS department!
cs.ox.ac.uk/aboutus/vacancie…
Ed Wagstaff retweeted
I am looking for troublemakers who want to start a PhD in #probabilistic #ML #AI at @ancAtEd @InfAtEd @EdinburghUni to design the foundations for the next generations of #autonomous #systems.
Drop me an email or DM here!
Please share!
We have 14 funded places available on our PhD in Robotics and Autonomous Systems programme starting September 2022. More details and how to apply edinburgh-robotics.org/apply
Ed Wagstaff retweeted
Sign up to join discussions on some very interesting topics!
To name a couple:
- “I wish I knew … at the start of my research career”
- “Is deep learning the master algorithm?”
This event is hosted as part of the social program at #NeurIPS2021 😎😎
🥳 We are proud to present our second event of #RoundtableChatroom at #NeurIPS2021 @NeurIPSConf sponsored by @ivythread !
Save the date: 8-10PM GMT FRI 10 DEC, 2021 (ZOOM)
Sign-up: roundtable-chatroom.com/
Each discussion topic will be guided by a knowledgeable Mentor below ⬇️
Ed Wagstaff retweeted
Playing around with @sportsracer48's new notebook. Taking advantage of the optical flow features and water drops. Wild!
#VQGAN #vqganclip
Ed Wagstaff retweeted
Twitter, a favour. And yes, it's a pub not allowed to stay al fresco: The Ship Tavern in Holborn has been close to my heart for a while. It's a family-run pub in the middle of central London and it's been there since 1549. It also happens to be *beautiful*
Ed Wagstaff retweeted
I'm especially excited about potential use cases in healthcare. Here is an explanation of "how would this retinal image have to change in order for it to be considered diseased" --> shows that the disease classifier is detecting "clustered exudates" (the bright dots)
































